library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.6 ✓ dplyr 1.0.7
## ✓ tidyr 1.1.4 ✓ stringr 1.4.0
## ✓ readr 2.1.1 ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
# library(RColorBrewer)
library(ggpubr)
# library(egg)
## eval 代码要不要运行
## echo 代码要不要输出
## include 图要不要输出
## warning 警告要不要输出
## message 默认Bin等信息要不要输出df <- read_tsv("data/018_wholeGenomeScan/vmap2.1.posAllele_10000000window_1000000step.txt.gz")## Rows: 13864 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (3): BIN_START, BIN_END, Count
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
max(df$Count)## [1] 298228
min(df$Count)## [1] 2
# ## 写出 circos
# dfout <- df %>%
# mutate(BIN_START=)
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/001_snpDensity.txt",col_names = F)
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=Count/10000))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000), y= 3/40000 *max(df$Count)),
size=2.5)+
labs(x="Physical position (Mb)", y = "SNP count on the whole-genome (x10000)")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
scale_y_continuous(limits = c(0,30))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
p# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/test.pdf",height =3.6, width = 7.2)df <- read_tsv("data/018_wholeGenomeScan/003_gene_SNP_10000000window_1000000step.txt.gz")## Rows: 13859 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (5): BIN_START, BIN_END, Count, Ave, Sd
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
max(df$Count)## [1] 9081
min(df$Count)## [1] 0
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
# ### 写出 circos
# dfout <- df %>% select(CHROM,BIN_START,BIN_END,Count)
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/002_gene_snpDensity.txt",col_names = F)
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=Count))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000), y= 3/4 *max(df$Count)),
size=2.5)+
labs(x="Physical position (Mb)", y = "SNP count on the gene region")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
scale_y_continuous(limits = c(0,9000),breaks = c(0,2500,5000,7500))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
p## Warning: Removed 1 rows containing missing values (position_stack).
# ggsave(p,filename = "~/Documents/SNPcount_geneRegion.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/SNPcount_geneRegion.pdf",height =3.6, width = 7.2)## Warning: Removed 1 rows containing missing values (position_stack).
# df %>% ggplot(aes(x=df$Count))+
# geom_histogram()
# facet_wrap(~CHROM,ncol = 3)# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/007_merge006/GERP_more0_10000000window_1000000step.txt.gz") %>%
# filter(!is.na(Ave), is.finite(Ave))
df <- read_tsv("data/018_wholeGenomeScan/GERP_10000000window_1000000step.txt.gz") %>%
filter(!is.na(Ave), is.finite(Ave))## Rows: 13865 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (5): BIN_START, BIN_END, Count, Ave, Sd
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
max(df$Ave)## [1] 0.0962
min(df$Ave)## [1] -0.0217
# dfout <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/009_merge008/GERP_10000000window_1000000step.txt.gz") %>%
# filter(!is.na(Ave), is.finite(Ave)) %>%
# filter(Ave <= 0.08)
#
# ### 写出 circos
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,Ave) %>%
# mutate(Ave=format(Ave,scientific = FALSE)) %>%
# mutate(Ave=str_replace_all(Ave," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/003_GERP.txt",col_names = F)
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=Ave))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
y=0.06
# y= 3/4 *max(df$Ave)
),
size=2.5)+
labs(x="Physical position (Mb)", y = "GERP score")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0.4,1.05))+
scale_y_continuous(breaks = c(0,0.03,0.06,0.09))+
coord_cartesian(ylim = c(0,0.1))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
p# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/GERP_wholeGenomeScan.pdf",height =3.6, width = 7.2)# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/002_GERP/007_merge006/GERP_more0_10000000window_1000000step.txt.gz") %>%
# filter(!is.na(Ave), is.finite(Ave))
df <- read_tsv("data/018_wholeGenomeScan/003_PPH2_10000000window_1000000step.txt.gz") %>%
filter(!is.na(Ave), is.finite(Ave))## Rows: 13853 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (5): BIN_START, BIN_END, Count, Ave, Sd
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
max(df$Ave)## [1] 1
min(df$Ave)## [1] 5e-04
# ### 写出 circos
# dfout <- df %>% select(CHROM,BIN_START,BIN_END,Ave) %>%
# mutate(Ave=format(Ave,scientific = FALSE)) %>%
# mutate(Ave=str_replace_all(Ave," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/004_PPH2.txt",col_names = F)
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=Ave))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
y=0.6
# y= 3/4 *max(df$Ave)
),
size=2.5)+
labs(x="Physical position (Mb)", y = "PPH2 score")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0.4,1.05))+
scale_y_continuous(breaks = c(0,0.3,0.6,0.9))+
coord_cartesian(ylim = c(0,1))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
p# ggsave(p,filename = "~/Documents/test.pdf",height =7.2*0.618, width = 7.2)
ggsave(p,filename = "~/Documents/PPH2_wholeGenomeScan.pdf",height =3.6, width = 7.2)df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
filter(!is.na(DelSynRatio))## Rows: 14075 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (22): BIN_START, BIN_END, BIN_START_scale, a001_synonymous, a002_nonsyno...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio),is.finite(DelSynRatio))
#
# max(df$DelSynRatio)
# min(df$DelSynRatio)
#
# # ### 写出 circos
# dfout <- df %>%
# filter(!is.na(DelSynRatio), is.finite(DelSynRatio)) %>%
# filter(DelSynRatio <= 1.3)
#
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,DelSynRatio) %>%
# mutate(DelSynRatio=format(DelSynRatio,scientific = FALSE)) %>%
# mutate(DelSynRatio=str_replace_all(DelSynRatio," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/005_DelSynRatio.txt",col_names = F)
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=DelSynRatio))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
# y= 3/4 *max(df$DelSynRatio)
y=1.5
),
size=2.5)+
labs(x="Physical position (Mb)", y = "DelRatio")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0,4))+
coord_cartesian(ylim = c(0,2))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
pggsave(p,filename = "~/Documents/01-DelSynRatio.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
filter(!is.na(NonsynSynRatio)) %>%
filter(is.finite(NonsynSynRatio))## Rows: 14075 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (22): BIN_START, BIN_END, BIN_START_scale, a001_synonymous, a002_nonsyno...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(NonsynSynRatio)) %>%
# filter(is.finite(NonsynSynRatio))
#
# ### 0-4
# max(df$NonsynSynRatio)
# min(df$NonsynSynRatio)
#
# # ### 写出 circos
# dfout <- df %>%
# filter(!is.na(NonsynSynRatio), is.finite(NonsynSynRatio)) %>%
# filter(NonsynSynRatio <= 3)
#
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,NonsynSynRatio) %>%
# mutate(NonsynSynRatio=format(NonsynSynRatio,scientific = FALSE)) %>%
# mutate(NonsynSynRatio=str_replace_all(NonsynSynRatio," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/006_NonsynSynRatio.txt",col_names = F)
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=NonsynSynRatio))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
# y= 3/4 *max(df$DelSynRatio)
y=3
),
size=2.5)+
labs(x="Physical position (Mb)", y = "NonsynSynRatio")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0,4))+
scale_y_continuous(breaks = c(0,2,4))+
coord_cartesian(ylim = c(0,4))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
pggsave(p,filename = "~/Documents/02-NonsynSynRatio.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
filter(!is.na(DelFre)) %>%
filter(is.finite(DelFre))## Rows: 14075 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (22): BIN_START, BIN_END, BIN_START_scale, a001_synonymous, a002_nonsyno...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
### 0-4
max(df$DelFre)## [1] 0.002350622
min(df$DelFre)## [1] 0
# ### 写出 circos
# dfout <- df %>%
# filter(!is.na(DelFre), is.finite(DelFre)) %>%
# filter(DelFre != 0)
#
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,DelFre) %>%
# mutate(DelFre=format(DelFre,scientific = FALSE)) %>%
# mutate(DelFre=str_replace_all(DelFre," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/007_DelFre.txt",col_names = F)
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=DelFre))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
# y= 3/4 *max(df$DelSynRatio)
y=0.0015
),
size=2.5)+
labs(x="Physical position (Mb)", y = "DelFre")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0,4))+
scale_y_continuous(breaks = c(0,0.001,0.002))+
coord_cartesian(ylim = c(0,0.0025))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
pggsave(p,filename = "~/Documents/03-DelFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
filter(!is.na(NonsynFre)) %>%
filter(is.finite(NonsynFre))## Rows: 14075 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (22): BIN_START, BIN_END, BIN_START_scale, a001_synonymous, a002_nonsyno...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
### 0-4
max(df$NonsynFre)## [1] 0.01205793
min(df$NonsynFre)## [1] 0
# # ### 写出 circos
# dfout <- df %>%
# filter(!is.na(NonsynFre), is.finite(NonsynFre)) %>%
# filter(NonsynFre != 0)
#
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,NonsynFre) %>%
# mutate(NonsynFre=format(NonsynFre,scientific = FALSE)) %>%
# mutate(NonsynFre=str_replace_all(NonsynFre," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/008_NonsynFre.txt",col_names = F)
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=NonsynFre))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
# y= 3/4 *max(df$DelSynRatio)
y=0.006
),
size=2.5)+
labs(x="Physical position (Mb)", y = "NonsynFre")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0,4))+
scale_y_continuous(breaks = c(0,0.004,0.008))+
coord_cartesian(ylim = c(0,0.009))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
pggsave(p,filename = "~/Documents/04-NonsynFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")df <- read_tsv("data/006_Fig2/genomeScan/003_delVSsynOnChr_10000000window1000000step_addEffectiveCDSLength_addRecom.txt") %>%
filter(!is.na(SynFre)) %>%
filter(is.finite(SynFre))## Rows: 14075 Columns: 23
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: "\t"
## chr (1): CHROM
## dbl (22): BIN_START, BIN_END, BIN_START_scale, a001_synonymous, a002_nonsyno...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
### 0-4
max(df$SynFre)## [1] 0.01154103
min(df$SynFre)## [1] 0
# # # ### 写出 circos
# dfout <- df %>%
# filter(!is.na(SynFre), is.finite(SynFre)) %>%
# filter(SynFre != 0)
#
# dfout <- dfout %>% select(CHROM,BIN_START,BIN_END,SynFre) %>%
# mutate(SynFre=format(SynFre,scientific = FALSE)) %>%
# mutate(SynFre=str_replace_all(SynFre," ",""))
#
# write_tsv(dfout,"/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/019_circos/006_input_circos/009_SynFre.txt",col_names = F)
# df <- read_tsv("/Users/Aoyue/project/wheatVMap2_1000/002_dataAnalysis/004_annoDB/009_genomeScan_delvcSyn/002/001_delVSsynOnChr_20000000window5000000step_addEffectiveCDSLength.txt") %>%
# filter(!is.na(DelSynRatio))
#### 设置每条染色体的点
data1 <- data.frame(CHROM = paste(1:7,rep("A",7),sep = ""),x=c(213,327,319,266,254,286,362),y=rep(0,7))
data2 <- data.frame(CHROM = paste(1:7,rep("B",7),sep = ""),x=c(241,348,347,304,201,325,309),y=rep(0,7))
data3 <- data.frame(CHROM = paste(1:7,rep("D",7),sep = ""),x=c(170,268,240,185,187,215,339),y=rep(0,7))
data <- rbind(data1,data2,data3)
colB <- c("#fd8582","#967bce","#4bcdc6")
p <- df %>%
mutate(Sub=str_sub(CHROM,2,2)) %>%
ggplot(aes(x=BIN_START/1000000, y=SynFre))+
geom_line(aes(color=Sub),alpha = 0.95,size=0.2)+
geom_area(alpha=0.8,aes(fill=Sub)) +
geom_point(aes(x,y),color = "blue",size=1,data = data)+
geom_text(data = tibble(CHROM = unique(df$CHROM)),
aes(label = CHROM, x=median(df$BIN_START/1000000),
# y= 3/4 *max(df$DelSynRatio)
y=0.005
),
size=2.5)+
labs(x="Physical position (Mb)", y = "SynFre")+
scale_fill_manual(values = colB)+
scale_color_manual(values = colB)+
facet_wrap(~ CHROM,ncol = 3,strip.position = "right",scales = "free_y")+
# scale_y_continuous(limits = c(0,4))+
scale_y_continuous(breaks = c(0,0.004,0.008))+
coord_cartesian(ylim = c(0,0.009))+
theme_classic()+
theme(panel.grid = element_blank(),
panel.background = element_blank(),
axis.line = element_line(size=0.3, colour = "black"),
legend.position = 'none',
strip.text = element_blank(),
text = element_text(size = 9))
pggsave(p,filename = "~/Documents/05-SynFre.pdf",height =7.2*9/16, width = 7.2)
# ggsave(p,filename = "~/Documents/test2.pdf",height = 18, width = 33,units = "cm")circos -conf circosByAoyue.conf -outputdir ./